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Myopia is a leading cause of visual impairment and has raised significant international concern in recent decades with rapidly increasing prevalence and incidence worldwide. Accurate prediction of future myopia risk could help identify high-risk children for early targeted intervention to delay myopia onset or slow myopia progression. Researchers have built and assessed various myopia prediction models based on different datasets, including baseline refraction or biometric data, lifestyle data, genetic data, and data integration. Here, we summarize all related work published in the past 30 years and provide a comprehensive review of myopia prediction methods, datasets, and performance, which could serve as a useful reference and valuable guideline for future research.

Diabetic retinopathy (DR), a major microvascular complication of diabetes, has a significant impact on the world's health systems. Globally, the number of people with DR will grow from 126.6 million in 2010 to 191.0 million by 2030, and we estimate that the number with vision-threatening diabetic retinopathy (VTDR) will increase from 37.3 million to 56.3 million, if prompt action is not taken. Despite growing evidence documenting the effectiveness of routine DR screening and early treatment, DR frequently leads to poor visual functioning and represents the leading cause of blindness in working-age populations. DR has been neglected in health-care research and planning in many low-income countries, where access to trained eye-care professionals and tertiary eye-care services may be inadequate. Demand for, as well as, supply of services may be a problem. Rates of compliance with diabetes medications and annual eye examinations may be low, the reasons for which are multifactorial. Innovative and comprehensive approaches are needed to reduce the risk of vision loss by prompt diagnosis and early treatment of VTDR.

PurposeTo explore intergenerational changes in the myopia epidemic in China in a sample of twins and their parents.MethodsLongitudinal cohort study. A total of 686 children with baseline age from 7 to 15 years were followed annually from 2006 to 2018. Cycloplegic refractions and ocular biometry of the children and non-cycloplegic refractions and ocular biometry of the parents were measured.ResultsThe myopia prevalence in the young adult children was 78.0%, while it was 42.1% in the parents. The prevalence of high myopia (9.6% vs 5.2%) and moderate myopia (38.8% vs 9.9%) was higher in the children, while the percentage of mild hyperopia (9.5% vs 16.3%) and emmetropia (10.6% vs 40.0%) was lower. No significant difference was found in extremely high myopia (2.2% vs 1.9%) and severe hyperopia (1.9% vs 1.6%). The distribution of refraction in the younger generation had a marked plateau in the zone of −6.0 D to −0.5 D, rather than the tighter peak around −1.0 D in parents. The correlation between the percentile position in the distributions of refraction of the parents and children was low (about 0.30). The distribution of axial length changed significantly, but there was little change in lens power, corneal power and corneal radius of curvature.ConclusionsMajor increases in the prevalence and severity of myopia between generations in China are largely due to increased axial elongation in the children. These increases are consistent with the known causal impacts of increased educational pressures and decreased time outdoors.

AimTo develop a deep learning (DL) model that predicts age from fundus images (retinal age) and to investigate the association between retinal age gap (retinal age predicted by DL model minus chronological age) and mortality risk.MethodsA total of 80 169 fundus images taken from 46 969 participants in the UK Biobank with reasonable quality were included in this study. Of these, 19 200 fundus images from 11 052 participants without prior medical history at the baseline examination were used to train and validate the DL model for age prediction using fivefold cross-validation. A total of 35 913 of the remaining 35 917 participants had available mortality data and were used to investigate the association between retinal age gap and mortality.ResultsThe DL model achieved a strong correlation of 0.81 (p<0·001) between retinal age and chronological age, and an overall mean absolute error of 3.55 years. Cox regression models showed that each 1 year increase in the retinal age gap was associated with a 2% increase in risk of all-cause mortality (hazard ratio (HR)=1.02, 95% CI 1.00 to 1.03, p=0.020) and a 3% increase in risk of cause-specific mortality attributable to non-cardiovascular and non-cancer disease (HR=1.03, 95% CI 1.00 to 1.05, p=0.041) after multivariable adjustments. No significant association was identified between retinal age gap and cardiovascular- or cancer-related mortality.ConclusionsOur findings indicate that retinal age gap might be a potential biomarker of ageing that is closely related to risk of mortality, implying the potential of retinal image as a screening tool for risk stratification and delivery of tailored interventions.

This study investigated the diagnostic performance, feasibility, and end-user experiences of an artificial intelligence (AI)-assisted diabetic retinopathy (DR) screening model in real-world Australian healthcare settings. The study consisted of two components: (1) DR screening of patients using an AI-assisted system and (2) in-depth interviews with health professionals involved in implementing screening. Participants with type 1 or type 2 diabetes mellitus attending two endocrinology outpatient and three Aboriginal Medical Services clinics between March 2018 and May 2019 were invited to a prospective observational study. A single 45-degree (macula centred), non-stereoscopic, colour retinal image was taken of each eye from participants and were instantly screened for referable DR using a custom offline automated AI system. A total of 236 participants, including 174 from endocrinology and 62 from Aboriginal Medical Services clinics, provided informed consent and 203 (86.0%) were included in the analysis. A total of 33 consenting participants (14%) were excluded from the primary analysis due to ungradable or missing images from small pupils (n = 21, 63.6%), cataract (n = 7, 21.2%), poor fixation (n = 2, 6.1%), technical issues (n = 2, 6.1%), and corneal scarring (n = 1, 3%). The area under the curve, sensitivity, and specificity of the AI system for referable DR were 0.92, 96.9% and 87.7%, respectively. There were 51 disagreements between the reference standard and index test diagnoses, including 29 which were manually graded as ungradable, 21 false positives, and one false negative. A total of 28 participants (11.9%) were referred for follow-up based on new ocular findings, among whom, 15 (53.6%) were able to be contacted and 9 (60%) adhered to referral. Of 207 participants who completed a satisfaction questionnaire, 93.7% specified they were either satisfied or extremely satisfied, and 93.2% specified they would be likely or extremely likely to use this service again. Clinical staff involved in screening most frequently noted that the AI system was easy to use, and the real-time diagnostic report was useful. Our study indicates that AI-assisted DR screening model is accurate and well-accepted by patients and clinicians in endocrinology and indigenous healthcare settings. Future deployments of AI-assisted screening models would require consideration of downstream referral pathways.

ObjectiveThis study was to aggregate the prevalence and risks of epiretinal membranes (ERMs) and determine the possible causes of the varied estimates.DesignSystematic review and meta-analysis.Data sourcesThe search strategy was designed prospectively. We searched PubMed, Embase and Web of Science databases from inception to July 2016. Reference lists of the included literatures were reviewed as well.Study selectionSurveys published in English language from any population were included if they had a population-based design and reported the prevalence of ERM from retinal photography with or without optical coherence tomography. Eligibility and quality evaluation was conducted independently by two investigators.Data extractionThe literature search generated 2144 records, and 13 population-based studies comprising 49 697 subjects were finally included. The prevalence of ERM and the ORs of potential risk factors (age, sex, myopia, hypertension and so on) were extracted.ResultsThe pooled age-standardised prevalence estimates of earlier ERM (cellophane macular reflex (CMR)), advanced ERM (preretinal macular fibrosis (PMF)) and any ERM were 6.5% (95% CI 4.2% to 8.9%), 2.6% (95% CI 1.8% to 3.4%) and 9.1% (95% CI 6.0% to 12.2%), respectively. In the subgroup analysis, race and photography modality contributed to the variation in the prevalence estimates of PMF, while the WHO regions and image reading methods were associated with the varied prevalence of CMR and any ERM. Meta-analysis showed that only greater age and female significantly conferred a higher risk of ERMs.ConclusionsOur findings suggest that ERMs are relatively common among aged population. Race, image taking and reading methodology may play important roles in influencing the large variability of ERM prevalence estimates.

ObjectivesTo explore associations between visual impairment (VI) and mortality in an adult population in urban China.MethodsThe Liwan Eye Study was a population-based prevalence survey conducted in Guangzhou, Southern China. The baseline examination was carried out in 2003. All baseline participants were invited for the 10-year follow-up visit. VI was defined as the visual acuity of 20/40 or worse in the better-seeing eye with habitual correction if worn. Correctable VI was defined as the VI correctable to 20/40 or better by subjective refraction, and non-correctable VI was defined as the VI correctable to worse than 20/40. Mortality rates were compared using the log-rank test and Cox proportional hazards regression models.ResultsOf the 1399 participants (mean age: 65.3 ± 9.93 years; 56.4% female) with available baseline visual acuity measurement, 320 participants (22.9%) had VI. After 10 years, 314 (22.4%) participants died. Visually impaired participants had a significantly increased 10-year mortality compared with those without VI (40.0% vs. 17.2%, P < 0.05). After adjusting for age, gender, income, educational attainment, BMI, history of diabetes and hypertension, both VI (HR, 1.55; 95% CI, 1.14–2.11) and non-correctable VI (HR, 2.72; 95% CI, 1.86–3.98) were significantly associated with poorer survival, while correctable VI (HR, 0.99; 95% CI, 0.66–1.49) was not an independent risk factor for 10-year mortality.ConclusionsOur findings that VI, particularly non-correctable VI, predicting poorer survival may imply the underlying mechanism behind VI-mortality association and reinforce the importance of preventing and treating disabling ocular diseases to prevent premature mortality in the elderly.

Myopia, also known as short-sightedness or near-sightedness, is a very common condition that typically starts in childhood. Severe forms of myopia (pathologic myopia) are associated with a risk of other associated ophthalmic problems. This disorder affects all populations and is reaching epidemic proportions in East Asia, although there are differences in prevalence between countries. Myopia is caused by both environmental and genetic risk factors. A range of myopia management and control strategies are available that can treat this condition, but it is clear that understanding the factors involved in delaying myopia onset and slowing its progression will be key to reducing the rapid rise in its global prevalence. To achieve this goal, improved data collection using wearable technology, in combination with collection and assessment of data on demographic, genetic and environmental risk factors and with artificial intelligence are needed. Improved public health strategies focusing on early detection or prevention combined with additional effective therapeutic interventions to limit myopia progression are also needed. This Primer by Baird, He and colleagues reviews the epidemiology, pathophysiology, diagnosis and treatment of myopia, a prevalent eye disorder among school-aged children that affects distance vision and may result in irreversible visual impairment.

The purpose of this study is to evaluate the feasibility and patient acceptability of a novel artificial intelligence (AI)-based diabetic retinopathy (DR) screening model within endocrinology outpatient settings. Adults with diabetes were recruited from two urban endocrinology outpatient clinics and single-field, non-mydriatic fundus photographs were taken and graded for referable DR ( ≥ pre-proliferative DR). Each participant underwent; (1) automated screening model; where a deep learning algorithm (DLA) provided real-time reporting of results; and (2) manual model where retinal images were transferred to a retinal grading centre and manual grading outcomes were distributed to the patient within 2 weeks of assessment. Participants completed a questionnaire on the day of examination and 1-month following assessment to determine overall satisfaction and the preferred model of care. In total, 96 participants were screened for DR and the mean assessment time for automated screening was 6.9 minutes. Ninety-six percent of participants reported that they were either satisfied or very satisfied with the automated screening model and 78% reported that they preferred the automated model over manual. The sensitivity and specificity of the DLA for correct referral was 92.3% and 93.7%, respectively. AI-based DR screening in endocrinology outpatient settings appears to be feasible and well accepted by patients.

Myopia (near-sightedness) is an important public health issue. Spending more time outdoors can prevent myopia but the long-term association between this exposure and myopia has not been well characterised. We investigated the relationship between time spent outdoors in childhood, adolescence and young adulthood and risk of myopia in young adulthood. The Kidskin Young Adult Myopia Study (KYAMS) was a follow-up of the Kidskin Study, a sun exposure-intervention study of 1776 children aged 6–12 years. Myopia status was assessed in 303 (17.6%) KYAMS participants (aged 25–30 years) and several subjective and objective measures of time spent outdoors were collected in childhood (8–12 years) and adulthood. Index measures of total, childhood and recent time spent outdoors were developed using confirmatory factor analysis. Logistic regression was used to assess the association between a 0.1-unit change in the time outdoor indices and risk of myopia after adjusting for sex, education, outdoor occupation, parental myopia, parental education, ancestry and Kidskin Study intervention group. Spending more time outdoors during childhood was associated with reduced risk of myopia in young adulthood (multivariable odds ratio [OR] 0.82, 95% confidence interval [CI] 0.69, 0.98). Spending more time outdoors in later adolescence and young adulthood was associated with reduced risk of late-onset myopia (≥ 15 years of age, multivariable OR 0.79, 95% CI 0.64, 0.98). Spending more time outdoors in both childhood and adolescence was associated with less myopia in young adulthood.